This application generally relates to image processing, and more particularly, identifying and correcting errors in pointing solutions for persistent observation sensors.
There is a desire to collect persistent video (i.e., multiple image sequences) of a target from overhead platform-based (e.g., airborne or space-based) sensors that can easily be viewed, and/or interpreted, via displays. This may be especially important for military personnel and/or for other persons, using portable devices that may have limited processing capabilities. Conventional persistent video sensors generally stay fixed to (or focus on) a single point, for instance, on the ground, while the overhead platform is in motion.
The motion of the platform, however, causes changes in scale, perspective (e.g. parallax), rotation, and/or other changes in viewing geometry. These changes can complicate or prevent human and/or machine interpretation of targets, features, and threats. Conventional persistent video relies on human interpretation to ignore changes in the measured scene that result from platform motion and/or imperfect sensor staring.
Prior approaches that attempt to correct for errors in pointing solutions have included very computationally intensive and laborious techniques for iteratively determining platform location and sensor boresight pointing. U.S. Pat. No. 8,471,915, issued Jun. 25, 2013, entitled “Self-Correcting Adaptive Long-Stare Electro-Optical System”, and herein incorporated by reference in its entirety, discloses techniques for calculating transformations to prevent image intra-frame distortion caused by a relative motion between the scene and the imaging platform, and preventing geometric differences from manifesting as smear within an integration time, thus preventing intra-frame distortion. However, this system relies upon controlling an optical element based on the transformation to prevent the image distortion, and may require more computations for intra-frame motion prevention.
Thus, systems and methods for providing feedback as to whether an electro-optical/infrared sensor is staring perfectly are desired without the aforementioned drawbacks. For example, a system that can determine whether errors exist in the sensor pointing solution, that may facilitate identification of one or more root cause(s) of such errors (e.g., biases in gimbal angle, trajectory error (particularly height, etc.), that can improving image quality by correcting such errors instantly and in future image acquisition in applications which are particularly susceptible to inter-frame changes (e.g., imaging platforms having a wide field of view and/or high angular rates of movement with respect to the ground) would be greatly appreciated.